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윤석준Sukjoon Yoon

숙명여자대학교

Biochim. Biophys. Acta-Rev. Cancer, Nov 24 2023, S0304-419X(23)00179-8 | https://doi.org/10.1016/j.bbcan.2023.189030 Current advances in comprehensive omics data mining for oncology and cancer research

Euna Jeong ^a, Sukjoon Yoon ^a,b

^aResearch Institute of Women's Health, Sookmyung Women's University, Seoul 04310, Republic of Korea

^bDepartment of Biological Sciences, Sookmyung Women's University, Seoul 04310, Republic of Korea

Corresponding author : Sukjoon Yoon

Abstract

The availability of a large amount of multiomics data enables data-driven discovery studies on cancers. High-throughput data on mutations, gene/protein expression, immune scores (tumor-infiltrating cells), drug screening, and RNAi (shRNAs and CRISPRs) screening are major integrated components of patient samples and cell line datasets. Improvements in data access and user interfaces make it easy for general scientists to carry out their data mining practices on integrated multiomics data platforms without computational expertise. Here, we summarize the extent of data integration and functionality of several portals and software that provide integrated multiomics data mining platforms for all cancer studies. Recent progress includes programming interfaces (APIs) for customized data mining. Precalculated datasets assist noncomputational users in quickly browsing data associations. Furthermore, stand-alone software provides fast calculations and smart functions, guiding optimal sampling and filtering options for the easy discovery of significant data associations. These efforts improve the utility of cancer omics big data for noncomputational users at all levels of cancer research. In the present review, we aim to provide analytical information guiding general scientists to find and utilize data mining tools for their research.

논문정보

형식Review Paper
게재일2023년 11월 (BRIC 등록일 2023-12-06)
연구진국내 연구진
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